Once viewed as a futuristic technological concept that was forever over the horizon, autonomous vehicles are now widely considered an imminent inevitability. Advances in sensor technologies and control systems have spawned a proliferation of Advanced Driver Assistance Systems (ADAS) in current-generation vehicles, including adaptive cruise control (ACC), parking assistance (e.g., automatic parallel parking), blind spot monitoring and land change assistance, forward collision warning, and lane departure warning.
The even more advanced artificial intelligence systems onboard the next-generation vehicles currently under development go far beyond assistance, promising fully autonomous operation of the vehicle. Indeed the sensor and control systems onboard soon-to-be-released autonomous vehicle designs can safely navigate the vast majority of driving situations without human input at all.
Yet even the most optimistic of autonomous vehicle designers concede that substantial challenges remain. In particular, even the most advanced autonomous vehicles under development struggle to properly navigate highly anomalous, less-frequently encountered “edge cases”. And despite extensive internal representations of traffic regulations, autonomous vehicles possess a limited ability to adequately respond to spatial and temporal variations in regulatory frameworks.